| // Copyright 2023 Google LLC |
| // |
| // Licensed under the Apache License, Version 2.0 (the "License"); |
| // you may not use this file except in compliance with the License. |
| // You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
| // distributed under the License is distributed on an "AS IS" BASIS, |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| // See the License for the specific language governing permissions and |
| // limitations under the License. |
| |
| // Code generated by protoc-gen-go. DO NOT EDIT. |
| // versions: |
| // protoc-gen-go v1.33.0 |
| // protoc v4.25.3 |
| // source: google/cloud/aiplatform/v1beta1/data_labeling_job.proto |
| |
| package aiplatformpb |
| |
| import ( |
| reflect "reflect" |
| sync "sync" |
| |
| _ "google.golang.org/genproto/googleapis/api/annotations" |
| status "google.golang.org/genproto/googleapis/rpc/status" |
| money "google.golang.org/genproto/googleapis/type/money" |
| protoreflect "google.golang.org/protobuf/reflect/protoreflect" |
| protoimpl "google.golang.org/protobuf/runtime/protoimpl" |
| structpb "google.golang.org/protobuf/types/known/structpb" |
| timestamppb "google.golang.org/protobuf/types/known/timestamppb" |
| ) |
| |
| const ( |
| // Verify that this generated code is sufficiently up-to-date. |
| _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) |
| // Verify that runtime/protoimpl is sufficiently up-to-date. |
| _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) |
| ) |
| |
| // Sample strategy decides which subset of DataItems should be selected for |
| // human labeling in every batch. |
| type SampleConfig_SampleStrategy int32 |
| |
| const ( |
| // Default will be treated as UNCERTAINTY. |
| SampleConfig_SAMPLE_STRATEGY_UNSPECIFIED SampleConfig_SampleStrategy = 0 |
| // Sample the most uncertain data to label. |
| SampleConfig_UNCERTAINTY SampleConfig_SampleStrategy = 1 |
| ) |
| |
| // Enum value maps for SampleConfig_SampleStrategy. |
| var ( |
| SampleConfig_SampleStrategy_name = map[int32]string{ |
| 0: "SAMPLE_STRATEGY_UNSPECIFIED", |
| 1: "UNCERTAINTY", |
| } |
| SampleConfig_SampleStrategy_value = map[string]int32{ |
| "SAMPLE_STRATEGY_UNSPECIFIED": 0, |
| "UNCERTAINTY": 1, |
| } |
| ) |
| |
| func (x SampleConfig_SampleStrategy) Enum() *SampleConfig_SampleStrategy { |
| p := new(SampleConfig_SampleStrategy) |
| *p = x |
| return p |
| } |
| |
| func (x SampleConfig_SampleStrategy) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (SampleConfig_SampleStrategy) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_enumTypes[0].Descriptor() |
| } |
| |
| func (SampleConfig_SampleStrategy) Type() protoreflect.EnumType { |
| return &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_enumTypes[0] |
| } |
| |
| func (x SampleConfig_SampleStrategy) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use SampleConfig_SampleStrategy.Descriptor instead. |
| func (SampleConfig_SampleStrategy) EnumDescriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescGZIP(), []int{2, 0} |
| } |
| |
| // DataLabelingJob is used to trigger a human labeling job on unlabeled data |
| // from the following Dataset: |
| type DataLabelingJob struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Output only. Resource name of the DataLabelingJob. |
| Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` |
| // Required. The user-defined name of the DataLabelingJob. |
| // The name can be up to 128 characters long and can consist of any UTF-8 |
| // characters. |
| // Display name of a DataLabelingJob. |
| DisplayName string `protobuf:"bytes,2,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"` |
| // Required. Dataset resource names. Right now we only support labeling from a |
| // single Dataset. Format: |
| // `projects/{project}/locations/{location}/datasets/{dataset}` |
| Datasets []string `protobuf:"bytes,3,rep,name=datasets,proto3" json:"datasets,omitempty"` |
| // Labels to assign to annotations generated by this DataLabelingJob. |
| // |
| // Label keys and values can be no longer than 64 characters |
| // (Unicode codepoints), can only contain lowercase letters, numeric |
| // characters, underscores and dashes. International characters are allowed. |
| // See https://goo.gl/xmQnxf for more information and examples of labels. |
| // System reserved label keys are prefixed with "aiplatform.googleapis.com/" |
| // and are immutable. |
| AnnotationLabels map[string]string `protobuf:"bytes,12,rep,name=annotation_labels,json=annotationLabels,proto3" json:"annotation_labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"` |
| // Required. Number of labelers to work on each DataItem. |
| LabelerCount int32 `protobuf:"varint,4,opt,name=labeler_count,json=labelerCount,proto3" json:"labeler_count,omitempty"` |
| // Required. The Google Cloud Storage location of the instruction pdf. This |
| // pdf is shared with labelers, and provides detailed description on how to |
| // label DataItems in Datasets. |
| InstructionUri string `protobuf:"bytes,5,opt,name=instruction_uri,json=instructionUri,proto3" json:"instruction_uri,omitempty"` |
| // Required. Points to a YAML file stored on Google Cloud Storage describing |
| // the config for a specific type of DataLabelingJob. The schema files that |
| // can be used here are found in the |
| // https://storage.googleapis.com/google-cloud-aiplatform bucket in the |
| // /schema/datalabelingjob/inputs/ folder. |
| InputsSchemaUri string `protobuf:"bytes,6,opt,name=inputs_schema_uri,json=inputsSchemaUri,proto3" json:"inputs_schema_uri,omitempty"` |
| // Required. Input config parameters for the DataLabelingJob. |
| Inputs *structpb.Value `protobuf:"bytes,7,opt,name=inputs,proto3" json:"inputs,omitempty"` |
| // Output only. The detailed state of the job. |
| State JobState `protobuf:"varint,8,opt,name=state,proto3,enum=google.cloud.aiplatform.v1beta1.JobState" json:"state,omitempty"` |
| // Output only. Current labeling job progress percentage scaled in interval |
| // [0, 100], indicating the percentage of DataItems that has been finished. |
| LabelingProgress int32 `protobuf:"varint,13,opt,name=labeling_progress,json=labelingProgress,proto3" json:"labeling_progress,omitempty"` |
| // Output only. Estimated cost(in US dollars) that the DataLabelingJob has |
| // incurred to date. |
| CurrentSpend *money.Money `protobuf:"bytes,14,opt,name=current_spend,json=currentSpend,proto3" json:"current_spend,omitempty"` |
| // Output only. Timestamp when this DataLabelingJob was created. |
| CreateTime *timestamppb.Timestamp `protobuf:"bytes,9,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"` |
| // Output only. Timestamp when this DataLabelingJob was updated most recently. |
| UpdateTime *timestamppb.Timestamp `protobuf:"bytes,10,opt,name=update_time,json=updateTime,proto3" json:"update_time,omitempty"` |
| // Output only. DataLabelingJob errors. It is only populated when job's state |
| // is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. |
| Error *status.Status `protobuf:"bytes,22,opt,name=error,proto3" json:"error,omitempty"` |
| // The labels with user-defined metadata to organize your DataLabelingJobs. |
| // |
| // Label keys and values can be no longer than 64 characters |
| // (Unicode codepoints), can only contain lowercase letters, numeric |
| // characters, underscores and dashes. International characters are allowed. |
| // |
| // See https://goo.gl/xmQnxf for more information and examples of labels. |
| // System reserved label keys are prefixed with "aiplatform.googleapis.com/" |
| // and are immutable. Following system labels exist for each DataLabelingJob: |
| // |
| // - "aiplatform.googleapis.com/schema": output only, its value is the |
| // [inputs_schema][google.cloud.aiplatform.v1beta1.DataLabelingJob.inputs_schema_uri]'s |
| // title. |
| Labels map[string]string `protobuf:"bytes,11,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"` |
| // The SpecialistPools' resource names associated with this job. |
| SpecialistPools []string `protobuf:"bytes,16,rep,name=specialist_pools,json=specialistPools,proto3" json:"specialist_pools,omitempty"` |
| // Customer-managed encryption key spec for a DataLabelingJob. If set, this |
| // DataLabelingJob will be secured by this key. |
| // |
| // Note: Annotations created in the DataLabelingJob are associated with |
| // the EncryptionSpec of the Dataset they are exported to. |
| EncryptionSpec *EncryptionSpec `protobuf:"bytes,20,opt,name=encryption_spec,json=encryptionSpec,proto3" json:"encryption_spec,omitempty"` |
| // Parameters that configure the active learning pipeline. Active learning |
| // will label the data incrementally via several iterations. For every |
| // iteration, it will select a batch of data based on the sampling strategy. |
| ActiveLearningConfig *ActiveLearningConfig `protobuf:"bytes,21,opt,name=active_learning_config,json=activeLearningConfig,proto3" json:"active_learning_config,omitempty"` |
| } |
| |
| func (x *DataLabelingJob) Reset() { |
| *x = DataLabelingJob{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[0] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *DataLabelingJob) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*DataLabelingJob) ProtoMessage() {} |
| |
| func (x *DataLabelingJob) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[0] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use DataLabelingJob.ProtoReflect.Descriptor instead. |
| func (*DataLabelingJob) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescGZIP(), []int{0} |
| } |
| |
| func (x *DataLabelingJob) GetName() string { |
| if x != nil { |
| return x.Name |
| } |
| return "" |
| } |
| |
| func (x *DataLabelingJob) GetDisplayName() string { |
| if x != nil { |
| return x.DisplayName |
| } |
| return "" |
| } |
| |
| func (x *DataLabelingJob) GetDatasets() []string { |
| if x != nil { |
| return x.Datasets |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetAnnotationLabels() map[string]string { |
| if x != nil { |
| return x.AnnotationLabels |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetLabelerCount() int32 { |
| if x != nil { |
| return x.LabelerCount |
| } |
| return 0 |
| } |
| |
| func (x *DataLabelingJob) GetInstructionUri() string { |
| if x != nil { |
| return x.InstructionUri |
| } |
| return "" |
| } |
| |
| func (x *DataLabelingJob) GetInputsSchemaUri() string { |
| if x != nil { |
| return x.InputsSchemaUri |
| } |
| return "" |
| } |
| |
| func (x *DataLabelingJob) GetInputs() *structpb.Value { |
| if x != nil { |
| return x.Inputs |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetState() JobState { |
| if x != nil { |
| return x.State |
| } |
| return JobState_JOB_STATE_UNSPECIFIED |
| } |
| |
| func (x *DataLabelingJob) GetLabelingProgress() int32 { |
| if x != nil { |
| return x.LabelingProgress |
| } |
| return 0 |
| } |
| |
| func (x *DataLabelingJob) GetCurrentSpend() *money.Money { |
| if x != nil { |
| return x.CurrentSpend |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetCreateTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.CreateTime |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetUpdateTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.UpdateTime |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetError() *status.Status { |
| if x != nil { |
| return x.Error |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetLabels() map[string]string { |
| if x != nil { |
| return x.Labels |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetSpecialistPools() []string { |
| if x != nil { |
| return x.SpecialistPools |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetEncryptionSpec() *EncryptionSpec { |
| if x != nil { |
| return x.EncryptionSpec |
| } |
| return nil |
| } |
| |
| func (x *DataLabelingJob) GetActiveLearningConfig() *ActiveLearningConfig { |
| if x != nil { |
| return x.ActiveLearningConfig |
| } |
| return nil |
| } |
| |
| // Parameters that configure the active learning pipeline. Active learning will |
| // |
| // label the data incrementally by several iterations. For every iteration, it |
| // will select a batch of data based on the sampling strategy. |
| type ActiveLearningConfig struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Required. Max human labeling DataItems. The rest part will be labeled by |
| // machine. |
| // |
| // Types that are assignable to HumanLabelingBudget: |
| // |
| // *ActiveLearningConfig_MaxDataItemCount |
| // *ActiveLearningConfig_MaxDataItemPercentage |
| HumanLabelingBudget isActiveLearningConfig_HumanLabelingBudget `protobuf_oneof:"human_labeling_budget"` |
| // Active learning data sampling config. For every active learning labeling |
| // iteration, it will select a batch of data based on the sampling strategy. |
| SampleConfig *SampleConfig `protobuf:"bytes,3,opt,name=sample_config,json=sampleConfig,proto3" json:"sample_config,omitempty"` |
| // CMLE training config. For every active learning labeling iteration, system |
| // will train a machine learning model on CMLE. The trained model will be used |
| // by data sampling algorithm to select DataItems. |
| TrainingConfig *TrainingConfig `protobuf:"bytes,4,opt,name=training_config,json=trainingConfig,proto3" json:"training_config,omitempty"` |
| } |
| |
| func (x *ActiveLearningConfig) Reset() { |
| *x = ActiveLearningConfig{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[1] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *ActiveLearningConfig) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*ActiveLearningConfig) ProtoMessage() {} |
| |
| func (x *ActiveLearningConfig) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[1] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use ActiveLearningConfig.ProtoReflect.Descriptor instead. |
| func (*ActiveLearningConfig) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescGZIP(), []int{1} |
| } |
| |
| func (m *ActiveLearningConfig) GetHumanLabelingBudget() isActiveLearningConfig_HumanLabelingBudget { |
| if m != nil { |
| return m.HumanLabelingBudget |
| } |
| return nil |
| } |
| |
| func (x *ActiveLearningConfig) GetMaxDataItemCount() int64 { |
| if x, ok := x.GetHumanLabelingBudget().(*ActiveLearningConfig_MaxDataItemCount); ok { |
| return x.MaxDataItemCount |
| } |
| return 0 |
| } |
| |
| func (x *ActiveLearningConfig) GetMaxDataItemPercentage() int32 { |
| if x, ok := x.GetHumanLabelingBudget().(*ActiveLearningConfig_MaxDataItemPercentage); ok { |
| return x.MaxDataItemPercentage |
| } |
| return 0 |
| } |
| |
| func (x *ActiveLearningConfig) GetSampleConfig() *SampleConfig { |
| if x != nil { |
| return x.SampleConfig |
| } |
| return nil |
| } |
| |
| func (x *ActiveLearningConfig) GetTrainingConfig() *TrainingConfig { |
| if x != nil { |
| return x.TrainingConfig |
| } |
| return nil |
| } |
| |
| type isActiveLearningConfig_HumanLabelingBudget interface { |
| isActiveLearningConfig_HumanLabelingBudget() |
| } |
| |
| type ActiveLearningConfig_MaxDataItemCount struct { |
| // Max number of human labeled DataItems. |
| MaxDataItemCount int64 `protobuf:"varint,1,opt,name=max_data_item_count,json=maxDataItemCount,proto3,oneof"` |
| } |
| |
| type ActiveLearningConfig_MaxDataItemPercentage struct { |
| // Max percent of total DataItems for human labeling. |
| MaxDataItemPercentage int32 `protobuf:"varint,2,opt,name=max_data_item_percentage,json=maxDataItemPercentage,proto3,oneof"` |
| } |
| |
| func (*ActiveLearningConfig_MaxDataItemCount) isActiveLearningConfig_HumanLabelingBudget() {} |
| |
| func (*ActiveLearningConfig_MaxDataItemPercentage) isActiveLearningConfig_HumanLabelingBudget() {} |
| |
| // Active learning data sampling config. For every active learning labeling |
| // iteration, it will select a batch of data based on the sampling strategy. |
| type SampleConfig struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Decides sample size for the initial batch. initial_batch_sample_percentage |
| // is used by default. |
| // |
| // Types that are assignable to InitialBatchSampleSize: |
| // |
| // *SampleConfig_InitialBatchSamplePercentage |
| InitialBatchSampleSize isSampleConfig_InitialBatchSampleSize `protobuf_oneof:"initial_batch_sample_size"` |
| // Decides sample size for the following batches. |
| // following_batch_sample_percentage is used by default. |
| // |
| // Types that are assignable to FollowingBatchSampleSize: |
| // |
| // *SampleConfig_FollowingBatchSamplePercentage |
| FollowingBatchSampleSize isSampleConfig_FollowingBatchSampleSize `protobuf_oneof:"following_batch_sample_size"` |
| // Field to choose sampling strategy. Sampling strategy will decide which data |
| // should be selected for human labeling in every batch. |
| SampleStrategy SampleConfig_SampleStrategy `protobuf:"varint,5,opt,name=sample_strategy,json=sampleStrategy,proto3,enum=google.cloud.aiplatform.v1beta1.SampleConfig_SampleStrategy" json:"sample_strategy,omitempty"` |
| } |
| |
| func (x *SampleConfig) Reset() { |
| *x = SampleConfig{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[2] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *SampleConfig) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*SampleConfig) ProtoMessage() {} |
| |
| func (x *SampleConfig) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[2] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use SampleConfig.ProtoReflect.Descriptor instead. |
| func (*SampleConfig) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescGZIP(), []int{2} |
| } |
| |
| func (m *SampleConfig) GetInitialBatchSampleSize() isSampleConfig_InitialBatchSampleSize { |
| if m != nil { |
| return m.InitialBatchSampleSize |
| } |
| return nil |
| } |
| |
| func (x *SampleConfig) GetInitialBatchSamplePercentage() int32 { |
| if x, ok := x.GetInitialBatchSampleSize().(*SampleConfig_InitialBatchSamplePercentage); ok { |
| return x.InitialBatchSamplePercentage |
| } |
| return 0 |
| } |
| |
| func (m *SampleConfig) GetFollowingBatchSampleSize() isSampleConfig_FollowingBatchSampleSize { |
| if m != nil { |
| return m.FollowingBatchSampleSize |
| } |
| return nil |
| } |
| |
| func (x *SampleConfig) GetFollowingBatchSamplePercentage() int32 { |
| if x, ok := x.GetFollowingBatchSampleSize().(*SampleConfig_FollowingBatchSamplePercentage); ok { |
| return x.FollowingBatchSamplePercentage |
| } |
| return 0 |
| } |
| |
| func (x *SampleConfig) GetSampleStrategy() SampleConfig_SampleStrategy { |
| if x != nil { |
| return x.SampleStrategy |
| } |
| return SampleConfig_SAMPLE_STRATEGY_UNSPECIFIED |
| } |
| |
| type isSampleConfig_InitialBatchSampleSize interface { |
| isSampleConfig_InitialBatchSampleSize() |
| } |
| |
| type SampleConfig_InitialBatchSamplePercentage struct { |
| // The percentage of data needed to be labeled in the first batch. |
| InitialBatchSamplePercentage int32 `protobuf:"varint,1,opt,name=initial_batch_sample_percentage,json=initialBatchSamplePercentage,proto3,oneof"` |
| } |
| |
| func (*SampleConfig_InitialBatchSamplePercentage) isSampleConfig_InitialBatchSampleSize() {} |
| |
| type isSampleConfig_FollowingBatchSampleSize interface { |
| isSampleConfig_FollowingBatchSampleSize() |
| } |
| |
| type SampleConfig_FollowingBatchSamplePercentage struct { |
| // The percentage of data needed to be labeled in each following batch |
| // (except the first batch). |
| FollowingBatchSamplePercentage int32 `protobuf:"varint,3,opt,name=following_batch_sample_percentage,json=followingBatchSamplePercentage,proto3,oneof"` |
| } |
| |
| func (*SampleConfig_FollowingBatchSamplePercentage) isSampleConfig_FollowingBatchSampleSize() {} |
| |
| // CMLE training config. For every active learning labeling iteration, system |
| // will train a machine learning model on CMLE. The trained model will be used |
| // by data sampling algorithm to select DataItems. |
| type TrainingConfig struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // The timeout hours for the CMLE training job, expressed in milli hours |
| // i.e. 1,000 value in this field means 1 hour. |
| TimeoutTrainingMilliHours int64 `protobuf:"varint,1,opt,name=timeout_training_milli_hours,json=timeoutTrainingMilliHours,proto3" json:"timeout_training_milli_hours,omitempty"` |
| } |
| |
| func (x *TrainingConfig) Reset() { |
| *x = TrainingConfig{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[3] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TrainingConfig) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TrainingConfig) ProtoMessage() {} |
| |
| func (x *TrainingConfig) ProtoReflect() protoreflect.Message { |
| mi := &file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[3] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TrainingConfig.ProtoReflect.Descriptor instead. |
| func (*TrainingConfig) Descriptor() ([]byte, []int) { |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescGZIP(), []int{3} |
| } |
| |
| func (x *TrainingConfig) GetTimeoutTrainingMilliHours() int64 { |
| if x != nil { |
| return x.TimeoutTrainingMilliHours |
| } |
| return 0 |
| } |
| |
| var File_google_cloud_aiplatform_v1beta1_data_labeling_job_proto protoreflect.FileDescriptor |
| |
| var file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDesc = []byte{ |
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| } |
| |
| var ( |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescOnce sync.Once |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescData = file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDesc |
| ) |
| |
| func file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescGZIP() []byte { |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescOnce.Do(func() { |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescData) |
| }) |
| return file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDescData |
| } |
| |
| var file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_enumTypes = make([]protoimpl.EnumInfo, 1) |
| var file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes = make([]protoimpl.MessageInfo, 6) |
| var file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_goTypes = []interface{}{ |
| (SampleConfig_SampleStrategy)(0), // 0: google.cloud.aiplatform.v1beta1.SampleConfig.SampleStrategy |
| (*DataLabelingJob)(nil), // 1: google.cloud.aiplatform.v1beta1.DataLabelingJob |
| (*ActiveLearningConfig)(nil), // 2: google.cloud.aiplatform.v1beta1.ActiveLearningConfig |
| (*SampleConfig)(nil), // 3: google.cloud.aiplatform.v1beta1.SampleConfig |
| (*TrainingConfig)(nil), // 4: google.cloud.aiplatform.v1beta1.TrainingConfig |
| nil, // 5: google.cloud.aiplatform.v1beta1.DataLabelingJob.AnnotationLabelsEntry |
| nil, // 6: google.cloud.aiplatform.v1beta1.DataLabelingJob.LabelsEntry |
| (*structpb.Value)(nil), // 7: google.protobuf.Value |
| (JobState)(0), // 8: google.cloud.aiplatform.v1beta1.JobState |
| (*money.Money)(nil), // 9: google.type.Money |
| (*timestamppb.Timestamp)(nil), // 10: google.protobuf.Timestamp |
| (*status.Status)(nil), // 11: google.rpc.Status |
| (*EncryptionSpec)(nil), // 12: google.cloud.aiplatform.v1beta1.EncryptionSpec |
| } |
| var file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_depIdxs = []int32{ |
| 5, // 0: google.cloud.aiplatform.v1beta1.DataLabelingJob.annotation_labels:type_name -> google.cloud.aiplatform.v1beta1.DataLabelingJob.AnnotationLabelsEntry |
| 7, // 1: google.cloud.aiplatform.v1beta1.DataLabelingJob.inputs:type_name -> google.protobuf.Value |
| 8, // 2: google.cloud.aiplatform.v1beta1.DataLabelingJob.state:type_name -> google.cloud.aiplatform.v1beta1.JobState |
| 9, // 3: google.cloud.aiplatform.v1beta1.DataLabelingJob.current_spend:type_name -> google.type.Money |
| 10, // 4: google.cloud.aiplatform.v1beta1.DataLabelingJob.create_time:type_name -> google.protobuf.Timestamp |
| 10, // 5: google.cloud.aiplatform.v1beta1.DataLabelingJob.update_time:type_name -> google.protobuf.Timestamp |
| 11, // 6: google.cloud.aiplatform.v1beta1.DataLabelingJob.error:type_name -> google.rpc.Status |
| 6, // 7: google.cloud.aiplatform.v1beta1.DataLabelingJob.labels:type_name -> google.cloud.aiplatform.v1beta1.DataLabelingJob.LabelsEntry |
| 12, // 8: google.cloud.aiplatform.v1beta1.DataLabelingJob.encryption_spec:type_name -> google.cloud.aiplatform.v1beta1.EncryptionSpec |
| 2, // 9: google.cloud.aiplatform.v1beta1.DataLabelingJob.active_learning_config:type_name -> google.cloud.aiplatform.v1beta1.ActiveLearningConfig |
| 3, // 10: google.cloud.aiplatform.v1beta1.ActiveLearningConfig.sample_config:type_name -> google.cloud.aiplatform.v1beta1.SampleConfig |
| 4, // 11: google.cloud.aiplatform.v1beta1.ActiveLearningConfig.training_config:type_name -> google.cloud.aiplatform.v1beta1.TrainingConfig |
| 0, // 12: google.cloud.aiplatform.v1beta1.SampleConfig.sample_strategy:type_name -> google.cloud.aiplatform.v1beta1.SampleConfig.SampleStrategy |
| 13, // [13:13] is the sub-list for method output_type |
| 13, // [13:13] is the sub-list for method input_type |
| 13, // [13:13] is the sub-list for extension type_name |
| 13, // [13:13] is the sub-list for extension extendee |
| 0, // [0:13] is the sub-list for field type_name |
| } |
| |
| func init() { file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_init() } |
| func file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_init() { |
| if File_google_cloud_aiplatform_v1beta1_data_labeling_job_proto != nil { |
| return |
| } |
| file_google_cloud_aiplatform_v1beta1_encryption_spec_proto_init() |
| file_google_cloud_aiplatform_v1beta1_job_state_proto_init() |
| if !protoimpl.UnsafeEnabled { |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*DataLabelingJob); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*ActiveLearningConfig); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*SampleConfig); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TrainingConfig); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| } |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[1].OneofWrappers = []interface{}{ |
| (*ActiveLearningConfig_MaxDataItemCount)(nil), |
| (*ActiveLearningConfig_MaxDataItemPercentage)(nil), |
| } |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes[2].OneofWrappers = []interface{}{ |
| (*SampleConfig_InitialBatchSamplePercentage)(nil), |
| (*SampleConfig_FollowingBatchSamplePercentage)(nil), |
| } |
| type x struct{} |
| out := protoimpl.TypeBuilder{ |
| File: protoimpl.DescBuilder{ |
| GoPackagePath: reflect.TypeOf(x{}).PkgPath(), |
| RawDescriptor: file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDesc, |
| NumEnums: 1, |
| NumMessages: 6, |
| NumExtensions: 0, |
| NumServices: 0, |
| }, |
| GoTypes: file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_goTypes, |
| DependencyIndexes: file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_depIdxs, |
| EnumInfos: file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_enumTypes, |
| MessageInfos: file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_msgTypes, |
| }.Build() |
| File_google_cloud_aiplatform_v1beta1_data_labeling_job_proto = out.File |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_rawDesc = nil |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_goTypes = nil |
| file_google_cloud_aiplatform_v1beta1_data_labeling_job_proto_depIdxs = nil |
| } |